Flexible event ingestion framework in an event processing system

ABSTRACT

Systems and methods described herein are directed towards a flexible event ingestion framework. In some examples, an input source comprising information that identifies a plurality of events may be identified. Additionally, in some examples, an adapter for ingesting the information of the input source may be implemented. At least one additional component for modifying the adapter may be received. The adapter may be modified by implementing the at least one additional component with a transport component and a mapper component as part of ingesting the information. Further, a tuple for at least a first event may be generated based at least in part on the modified adapter, and the tuple may be provided to an event server.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation of International ApplicationNo. PCT/RU2015/000915, filed Dec. 23, 2015, the entire contents of whichis herein incorporated by reference for all purposes.

BACKGROUND

In traditional database systems, data is stored in one or more databasesusually in the form of tables. The stored data is then queried andmanipulated using a data management language such as a structured querylanguage (SQL). For example, a SQL query may be defined and executed toidentify relevant data from the data stored in the database. A SQL queryis thus executed on a finite set of data stored in the database.Further, when a SQL query is executed, it is executed once on the finitedata set and produces a finite static result. Databases are thus bestequipped to run queries over finite stored data sets.

A number of modern applications and systems however generate data in theform of continuous data or event streams instead of a finite data set.Examples of such applications include but are not limited to sensor dataapplications, financial tickers, network performance measuring tools(e.g. network monitoring and traffic management applications),clickstream analysis tools, automobile traffic monitoring, and the like.Such applications have given rise to a need for a new breed ofapplications that can process the data streams. For example, atemperature sensor may be configured to send out temperature readings.

Managing and processing data for these types of event stream-basedapplications involves building data management and querying capabilitieswith a strong temporal focus. A different kind of querying mechanism isneeded that comprises long-running queries over continuous unboundedsets of data. While some vendors now offer product suites geared towardsevent streams processing, these product offerings still lack theprocessing flexibility required for handling today's events processingneeds.

BRIEF SUMMARY

Embodiments described herein relate to event processing systems and, inparticular, to a flexible event ingestion framework that can beimplemented within at least one of the event processing systems.

According to some embodiments, a method, a computer-readable storagemedium, and/or a system may be implemented that includes identifying aninput source comprising information identifying a plurality of events,implementing an adapter for ingesting the information, receiving atleast one additional component for modifying the adapter, modifying theadapter by implementing the at least one additional component with thetransport component and the mapper component as part of ingesting theinformation, generating a tuple for at least the first event based atleast in part on the modified adapter, and providing the tuple to anevent server. In some examples, the adapter may comprise a transportcomponent that receives the information from the input source (e.g., inan Extensible Markup Language (XML) or a JavaScript Object Notation(JSON) file) and a mapper component that converts a first input type(e.g., XML data, JSON data, etc.) of a first event extracted from theinput source into a second input type (e.g., a tuple).

In some examples, the method, medium, and/or system may also enablecreation of the at least one additional component to customize theadapter for a particular input source. In some aspects, the at least oneadditional component for modifying the adapter may be received from asecond adapter different from the adapter implemented for ingesting theinformation and the second adapter may comprise a built-in adapter of anevent processing system configured to at least one of ingest theinformation of the input source or ingest a different set of data fromthe input source. Additionally, in some embodiments, the at least oneadditional component may comprise at least one of a trigger component,an extractor component, a filter component, a converter component, or achange detector component. The at least one additional component maycomprise a plurality of additional components, and the adapter may bemodified to implement at least a subset of the plurality of additionalcomponents along with the transport component and the mapper component.The trigger component may invoke the transport component to receive thecontents from the input stream. The extractor component may extractfields from the events from the input events converted by the mappercomponent. The filter component may filter the events from the inputevents based at least in part on a field of the event. The convertercomponent may convert a type of the event from the input event and thechange detector component may detect a change of the input content froma previous content received by the transport component. In someexamples, the change detector component may comprise at least one of acontent level change detector component or a tuple-level change detectorcomponent.

The foregoing, together with other features and embodiments will becomemore apparent upon referring to the following specification, claims, andaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified block diagram illustrating an examplearchitecture for implementing the flexible event ingestion frameworkdescribed herein, according to some embodiments.

FIG. 2 is a simplified block diagram illustrating at least some featuresof an event processing engine capable of handling continuous streams ofdata as described herein, according to at least one example.

FIG. 3 is another simplified block diagram illustrating another examplearchitecture for implementing the flexible event ingestion frameworkdescribed herein, according to some embodiments.

FIG. 4 is a simplified diagram illustrating an example class for tupleextraction as described herein, according to some embodiments.

FIG. 5 is a flow diagram illustrating an example of a technique forimplementing the flexible event ingestion framework described herein,according to some embodiments.

FIG. 6 is a simplified block diagram illustrating a distributed systemfor implementing some of the examples described herein, according to atleast one example.

FIG. 7 is a simplified block diagram illustrating components of a systemenvironment by which services provided by the components of anembodiment system may be offered as cloud services, in accordance withsome of the examples described herein, according to at least oneexample.

FIG. 8 is a simplified block diagram illustrating an example computersystem, in which various embodiments of the present disclosure may beimplemented in accordance with some of the examples described herein,according to at least one example.

DETAILED DESCRIPTION

In applications such as stock quote monitoring, automobile trafficmonitoring, and data sensing, data is generated in the form of a streamof events over time. A data stream, also referred to as an event stream,is a real-time, continuous, sequence of events. Examples of sources thatgenerate data streams include sensors and probes (e.g., radio frequencyidentification (RFID) sensors, temperature sensors, etc.) configured tosend a sequence of sensor readings, financial tickers, networkmonitoring and traffic management applications sending network status,click stream analysis tools, and others. The term “events” are usedinterchangeably with “tuples.” As used herein, tuples of a stream havethe same set of attributes but not necessarily the same attribute valuesfor those attributes. Each tuple is also associated with a particulartime. A tuple may be considered to be logically similar to a single rowor record in a relational database.

The event processing system typically has the adapter layer foringesting input events to the system. The primary responsibility of theadapter layer is to convert the input event types to tuple types thatthe event processing system understands. For converting input eventtypes to tuple types, the fields can be extracted from input event typeand set to tuple type. While extracting the fields, sometimes typeconversion is required. Since the extractor and the type conversionlogic should be able to handle any combination of inputs, the typicalimplementation uses many types of matching logic using if, else, switch,and map along with class types. Since the extraction is done for eachinput event and the type conversion is done for each field in the inputevent, the type conversion operation is critical.

In some examples, the adapter layer is configured to connect to certaintransport protocols and locations, and to convert input contents totuples. Since all event processing systems cannot support every possibleadapter, usually there is a way to write custom adapters by the users.However, the custom adapter framework provided by current evenprocessing systems have the following problems: they require too muchdetailed knowledge of the underlying system, the application programminginterfaces (APIs) are usually too low-level, and the components of eachcustom adapter cannot be reused.

In some examples, the following disclosure includes features builtwithin an adapter framework such as, but not limited to, a complex eventprocessing adapter framework (e.g., Oracle® Corporation's Oracle ComplexEvent Processing (OCEP) Adapter Framework); however, any the featuresdescribed may be implemented in any adapter framework. The featuresessentially abstract most of the adapter related components and allowsfor mix-ins (e.g., reusing adapter components from other frameworks orother custom adapters) of such components. As a result, it allows forthe creation of custom adapters without requiring too many mundanetasks. For example, for a Rich Site Summary (RSS) source, the followingcomponents may be utilized within an even processing system:

-   -   Read XML content from HTTP Transport    -   Convert XML content to event types    -   Extract individual events to tuples    -   Filter out unnecessary events    -   Handle and convert data formats    -   Re-load XML content with schedule    -   Check if the content is changed        However, with a typical adapter framework of even processing        system, each of those steps above would need to be manually        created by a customer.

To solve the issue, some adapter frameworks provide better abstraction,for example the following components may be utilized:

-   -   Transport: responsible to receive contents from the source    -   Mapper: responsible to convert one input type to another type    -   Trigger: invokes transport to receive content    -   Extractor: extracts fields    -   Filter: filters events based on fields    -   Converter: convert types of fields    -   Change Detector: detects change in contents/events

Additionally, with the mix-in features described herein, re-usingcomponents written from other custom adapters or provided from built-inadapters is possible.

The example below shows mix-ins of components to create the RSS sourcementioned above:

<bean id=“xmlMapperBean”class=“com.oracle.cep.adapter.mapper.jaxb.JAXBMapper” >    <propertyname=“metadata”value=“res://com.oracle.cep.adapter.nws.NWSSourceAdapter:/alertfeed.xml”/>  </bean> <bean id=“capChangeDetector”class=“com.oracle.cep.adapter.nws.CapChangeDetector”>  </bean> <beanid=“changeDetector”class=“com.oracle.cep.adapter.changedetector.MapChangeDetector”>  <property name=“eventTypeName” value=“AlertEntryEvent” />   <propertyname=“keyPropertyName” value=“id” />   <propertyname=“expirationPropertyName” value=“expires” />  </bean> <wlevs:adapterid=“AlertAreaAdapter” provider=“generic-source”>  <wlevs:instance-property name=“mapper” ref=“xmlMapperBean” />  <wlevs:instance-property name=“proxyHost”value=“www-proxy.us.oracle.com” />   <wlevs:instance-propertyname=“proxyPort” value=“80” />   <wlevs:instance-propertyname=“eventTypeName” value=“AlertFeed” />   <wlevs:instance-propertyname=“targetEventTypeName” value=“AlertEntryEvent” />  <wlevs:instance-property name=“converter”value=“com.oracle.cep.adapter.nws.GeomConverter;merge=false;simplify=0,com.oracle. cep.adapter.nws.TimeConverter” />   <wlevs:instance-propertyname=“extractRule” value=“foreach(AlertEntry:alerts,‘*;alertId=id;!id;effective=TimeConverter(effective);expires=TimeConverter(expires);geometry=GeomConverter(polygon,AlertGeocode:geocode/valueNames,AlertGeocode:geocode/values)’, ‘severity==Extreme;severity==Severe;severity==Moderate’,‘id=AutoSeq(0,alertId)’)” />   <wlevs:instance-property name=“sourceUrl”value=“http://alerts.weather.gov/cap/us.php?x=0” />  <wlevs:instance-property name=“contentChangeDetector”ref=“capChangeDetector” />   <wlevs:instance-propertyname=“changeDetector” ref=“changeDetector” /> </wlevs:adapter> <beanid=“fixedDelayedSchedule”class=“com.oracle.cep.adapter.trigger.Schedule”>  <constructor-argname=“delayInSec” value=“10000” />  <constructor-arg name=“periodInSec”value=“300000” />  <constructor-arg name=“key” value=“fixed_delay” /></bean> <bean id=“scheduleTrigger”class=“com.oracle.cep.adapter.trigger.ScheduledTrigger”>  <propertyname=“target” ref=“AlertAreaAdapter” />  <property name=“schedule”ref=“fixedDelayedSchedule” /> </bean>

Thus, with this solution, the following are new:

-   -   Flexible event ingestion framework    -   Allow mix-ins of components from an event processing network        (EPN)    -   Allow reusing of resources from other adapter

Prior to this solution, a user would need to write many repeatedcomponents to write a custom adapter. Additionally, these techniquesallow customers to write new custom adapter without writing much code byreusing existing components with mix-ins.

In some examples, creating a custom adapter may include implementing aJava class that communicates with the external component (source). Itmay also include implementing the interfaces that support sending orreceiving event type instances. If the adapter supports being suspendedand resumed, such as when it is undeployed and deployed, creating acustom adapter may also include implementing interfaces to handle theseevents. It may also include using multithreading to improve applicationscalability. For any required authentications, it may include writingJava logic to pass login credentials to the component that provides orreceives the event data. It may also include creating a factory classwhen multiple applications access the custom adapter.

The features described herein, therefore, aid in creation and reuse ofcustom adapter components by enabling the creation of a scheduledtrigger component, a field extractor component, a geometry convertercomponent (e.g., for geocoding), a filter component (e.g., to filter outcertain events), and/or a change detection component (e.g., forcontinuous RSS feeds).

In some examples, a transport component may be responsible for receivingcontents from the source. The contents may include more than one event.Additionally, a mapper component may be responsible for converting oneinput type to another type. The mapper component may use an extractorcomponent. In some examples, a trigger component may invoke thetransport component to receive content (events) from the source. Thetrigger component allows control of processing source data logic whenand what. It can provide an initial set of the source data and it canschedule extraction of data from the source. In some examples, theadapter only deals with processing data. Thus, it may be desirable toimplement a triggerable interface and follow some protocol. A scheduledtrigger may trigger on a schedule and/or may support “At,” “Delay,” and“Duration.” A folder monitor trigger may monitor folders and sendnew/updated file paths. A delay loopback trigger may support delay loadand/or delay repeat functionality. A console input trigger may retrieveinput from a console and may be useful in demo scenarios.

In some examples, an extractor component may be configured to extractfields. The extractor component may be implemented based at least inpart on a dynamically generated extractor class. Having a specificextractor component can enable adapter-specific extraction. Theextractor component can provide simple rules (including “foreach” rules)for extraction and can provide a mapping of properties (e.g., using aconverter). The extractor component may work with general ExtensibleStylesheet Language Transformation (XSLT) processing. Example of suchrules:

foreach(    AlertEntry:alerts,    ‘*;   geometry=GeomConverter(polygon,AlertGeocode:geocode/   valueNames,AlertGeocode:geocode/values’)That is, for each AlertEntry type in alerts of AlertFeed, the extractorcomponent may copy all properties but polygon, valueNames of geocodeproperty Of AlertGeocodeType, values of geocode property OfAlertGeocodeType passed to GeomConverter which creates a Geometry typeand assign it to geometry

In some examples, a filter component may be configured to filter eventsbased at least in part on fields of the events. The filter component maybe configured to filter based at least in part on event property. Thefilter component can support inclusion or can easily be expanded togeneral Boolean expression.

In some examples, a converter component may be configured to converttypes of fields. For example, property types may be automaticallyconverted for built-in types. Some geometry types may require moretreatment. For example, they may be spread into multiple properties,they may be complex type such as Extensible Markup Language (XML) orJavaScript Object Notation (JSON), and/or they may need geocodehandline. In some examples, a geometry converter may be configured forreceiving weather data or the like. The arguments may include a list ofgeocode names, a list of geocode values, and an optional list oflongitude/latitude pairs. For each geocode name/value, the adapter maydecode the geocode and get polygon data from a geocode database. Then,the geometry converter may return a list of geometries corresponding tothe geocode name/value pairs.

In some examples, a change detector component may be configured todetect changes in contents/events received by the custom adapter. Thechange detector component may detect changes of input events and sendevents of insert/update/delete kinds. In some examples, the changedetector may only work with Relation-type data; however, in otherexamples, it may work with all data types. The change detector componentmay be useful for working with sending updates from the same datasource(e.g., RSS). In some examples, the Key column from one of fields oftuple is required in order to detect insert/update/delete kinds. Oneembodiment of change detection component is using a hash table datastructure where the old events are stored in the hash table and the Keycolumn is to detect insert/update/delete kinds. Using a map changedetection component, the system may handle auto expiration from the timespecified in the event.

The techniques described above and below may be implemented in a numberof ways and in a number of contexts. Several example implementations andcontexts are provided with reference to the following figures, asdescribed below in more detail. However, the following implementationsand contexts are but a few of many.

FIG. 1 depicts a simplified example system or architecture 100 in whichtechniques for implementing a flexible event ingestion framework may beimplemented. In architecture 100, one or more users 102 (e.g., accountholders) may utilize user computing devices 104(1)-(N) (collectively,“user devices 104”) to access one or more service provider computers 106via one or more networks 108. In some aspects, the service providercomputers 106 may also be in communication with one or more streamingdata source computers 110 and/or one or more databases 112 via thenetworks 108. For example, the users 102 may utilize the serviceprovider computers 106 to access or otherwise manage data of thestreaming data source computers 110 and/or the databases 112 (e.g.,queries may be run against either or both of 110, 112). The databases112 may be relational databases, SQL servers, or the like and may, insome examples, manage historical data, event data, relations, archivedrelations, or the like on behalf of the users 102. Additionally, thedatabases 112 may receive or otherwise store data provided by thestreaming data source computers 110. In some examples, the users 102 mayutilize the user devices 104 to interact with the service providercomputers 106 by providing queries (also referred to as “querystatements”) or other requests for data (e.g., historical event data,streaming event data, etc.). Such queries or requests may then beexecuted by the service provider computers 106 to process data of thedatabases 112 and/or incoming data from the streaming data sourcecomputers 110. Further, in some examples, the streaming data sourcecomputers 110 and/or the databases 112 may be part of an integrated,distributed environment associated with the service provider computers106.

In some examples, the networks 108 may include any one or a combinationof multiple different types of networks, such as cable networks, theInternet, wireless networks, cellular networks, intranet systems, and/orother private and/or public networks. While the illustrated examplerepresents the users 102 accessing the service provider computers 106over the networks 108, the described techniques may equally apply ininstances where the users 102 interact with one or more service providercomputers 106 via the one or more user devices 104 over a landlinephone, via a kiosk, or in any other manner. It is also noted that thedescribed techniques may apply in other client/server arrangements(e.g., set-top boxes, etc.), as well as in non-client/serverarrangements (e.g., locally stored applications, etc.).

The user devices 104 may be any type of computing device such as, butnot limited to, a mobile phone, a smart phone, a personal digitalassistant (PDA), a laptop computer, a desktop computer, a thin-clientdevice, a tablet PC, etc. In some examples, the user devices 104 may bein communication with the service provider computers 106 via thenetworks 108, or via other network connections. Further, the userdevices 104 may also be configured to provide one or more queries orquery statements for requesting data of the databases 112 (or other datastores) to be processed.

In some aspects, the service provider computers 106 may also be any typeof computing devices such as, but not limited to, mobile, desktop,thin-client, and/or cloud computing devices, such as servers. In someexamples, the service provider computers 106 may be in communicationwith the user devices 104 via the networks 108, or via other networkconnections. The service provider computers 106 may include one or moreservers, perhaps arranged in a cluster, as a server farm, or asindividual servers not associated with one another. These servers may beconfigured to perform or otherwise host features described hereinincluding, but not limited to, the management of archived relations,configurable data windows associated with archived relations, and/oraccurately counting change events associated with managing archivedrelations described herein. Additionally, in some aspects, the serviceprovider computers 106 may be configured as part of an integrated,distributed computing environment that includes the streaming datasource computers 110 and/or the databases 112.

In one illustrative configuration, the service provider computers 106may include at least one memory 136 and one or more processing units (orprocessor(s)) 138. The processor(s) 138 may be implemented asappropriate in hardware, computer-executable instructions, firmware, orcombinations thereof. Computer-executable instruction or firmwareimplementations of the processor(s) 138 may include computer-executableor machine-executable instructions written in any suitable programminglanguage to perform the various functions described.

The memory 136 may store program instructions that are loadable andexecutable on the processor(s) 138, as well as data generated during theexecution of these programs. Depending on the configuration and type ofservice provider computers 106, the memory 136 may be volatile (such asrandom access memory (RAM)) and/or non-volatile (such as read-onlymemory (ROM), flash memory, etc.). The service provider computers 106 orservers may also include additional storage 140, which may includeremovable storage and/or non-removable storage. The additional storage140 may include, but is not limited to, magnetic storage, optical disks,and/or tape storage. The disk drives and their associatedcomputer-readable media may provide non-volatile storage ofcomputer-readable instructions, data structures, program modules, andother data for the computing devices. In some implementations, thememory 136 may include multiple different types of memory, such asstatic random access memory (SRAM), dynamic random access memory (DRAM),or ROM.

The memory 136, the additional storage 140, both removable andnon-removable, are all examples of computer-readable storage media. Forexample, computer-readable storage media may include volatile ornon-volatile, removable or non-removable media implemented in any methodor technology for storage of information such as computer-readableinstructions, data structures, program modules, or other data. Thememory 136 and the additional storage 140 are all examples of computerstorage media.

The service provider computers 106 may also contain communicationsconnection(s) 142 that allow the identity interface computers 120 tocommunicate with a stored database, another computing device or server,user terminals, and/or other devices on the networks 108. The serviceprovider computers 106 may also include input/output (I/O) device(s)144, such as a keyboard, a mouse, a pen, a voice input device, a touchinput device, a display, one or more speakers, a printer, etc.

Turning to the contents of the memory 136 in more detail, the memory 136may include an operating system 146 and one or more application programsor services for implementing the features disclosed herein including atleast an event ingestion module 148. As used herein, modules may referto programming modules executed by servers or clusters of servers thatare part of a service. In this particular context, the modules may beexecuted by the servers or clusters of servers that are part of theservice provider computers 106. In some examples, the event ingestionmodule 148 may be configured to identify an input stream of a pluralityof events, implement an adapter for ingesting the plurality of events ofthe input stream, receive at least one additional component formodifying the adapter, modify the adapter by implementing the at leastone additional component with the transport component and the mappercomponent as part of ingesting the plurality of events, generate a tuplefor at least the first event based at least in part on the modifiedadapter, and provide the tuple to an event server. In some examples, theadapter may comprise at least a transport component that receives atleast a first event of the plurality of events of the input stream and amapper component that converts a first input type of the first eventinto a second input type.

FIG. 2 depicts a simplified high level diagram of an event processingsystem 200 that may incorporate an embodiment of the present disclosure.Event processing system 200 may comprise one or more event sources (204,206, 208), an event processing server (EPS) 202 (also referred to as CQService 202) that is configured to provide an environment for processingevent streams, and one or more event sinks (210, 212). The event sourcesgenerate event streams that are received by EPS 202. EPS 202 may receiveone or more event streams from one or more event sources. For example,as shown in FIG. 2, EPS 202 receives an input event stream 214 fromevent source 204, a second input event stream 216 from event source 206,and a third event stream 218 from event source 208. One or more eventprocessing applications (220, 222, and 224) may be deployed on and beexecuted by EPS 202. An event processing application executed by EPS 202may be configured to listen to one or more input event streams, processthe events received via the one or more event streams based uponprocessing logic that selects one or more events from the input eventstreams as notable events. The notable events may then be sent to one ormore event sinks (210, 212) in the form of one or more output eventstreams. For example, in FIG. 2, EPS 202 outputs an output event stream226 to event sink 210, and a second output event stream 228 to eventsink 212. In certain embodiments, event sources, event processingapplications, and event sinks are decoupled from each other such thatone can add or remove any of these components without causing changes tothe other components.

In one embodiment, EPS 202 may be implemented as a Java servercomprising a lightweight Java application container, such as one basedupon Equinox OSGi, with shared services. In some embodiments, EPS 202may support ultra-high throughput and microsecond latency for processingevents, for example, by using JRockit Real Time. EPS 202 may alsoprovide a development platform (e.g., a complete real time end-to-endJava Event-Driven Architecture (EDA) development platform) includingtools (e.g., Oracle CEP Visualizer and Oracle CEP IDE) for developingevent processing applications.

An event processing application is configured to listen to one or moreinput event streams, execute logic (e.g., a query) for selecting one ormore notable events from the one or more input event streams, and outputthe selected notable events to one or more event sources via one or moreoutput event streams. FIG. 2 provides a drilldown for one such eventprocessing application 220. As shown in FIG. 2, event processingapplication 220 is configured to listen to input event stream 218,execute a query 230 comprising logic for selecting one or more notableevents from input event stream 218, and output the selected notableevents via output event stream 228 to event sink 212. Examples of eventsources include, without limitation, an adapter (e.g., JMS, HTTP, andfile), a channel, a processor, a table, a cache, and the like. Examplesof event sinks include, without limitation, an adapter (e.g., JMS, HTTP,and file), a channel, a processor, a cache, and the like.

Although event processing application 220 in FIG. 2 is shown aslistening to one input stream and outputting selected events via oneoutput stream, this is not intended to be limiting. In alternativeembodiments, an event processing application may be configured to listento multiple input streams received from one or more event sources,select events from the monitored streams, and output the selected eventsvia one or more output event streams to one or more event sinks. Thesame query can be associated with more than one event sink and withdifferent types of event sinks.

Due to its unbounded nature, the amount of data that is received via anevent stream is generally very large. Consequently, it is generallyimpractical and undesirable to store or archive all the data forquerying purposes. The processing of event streams requires processingof the events in real time as the events are received by EPS 202 withouthaving to store all the received events data. Accordingly, EPS 202provides a special querying mechanism that enables processing of eventsto be performed as the events are received by EPS 202 without having tostore all the received events.

Event-driven applications are rule-driven and these rules may beexpressed in the form of continuous queries that are used to processinput streams. A continuous query may comprise instructions (e.g.,business logic) that identify the processing to be performed forreceived events including what events are to be selected as notableevents and output as results of the query processing. Continuous queriesmay be persisted to a data store and used for processing input streamsof events and generating output streams of events. Continuous queriestypically perform filtering and aggregation functions to discover andextract notable events from the input event streams. As a result, thenumber of outbound events in an output event stream is generally muchlower than the number of events in the input event stream from which theevents are selected.

Unlike a SQL query that is run once on a finite data set, a continuousquery that has been registered by an application with EPS 202 for aparticular event stream may be executed each time that an event isreceived in that event stream. As part of the continuous queryexecution, EPS 202 evaluates the received event based upon instructionsspecified by the continuous query to determine whether one or moreevents are to be selected as notable events, and output as a result ofthe continuous query execution.

The continuous query may be programmed using different languages. Incertain embodiments, continuous queries may be configured using the CQLprovided by Oracle Corporation and used by Oracle's Complex EventsProcessing (CEP) product offerings. Oracle's CQL is a declarativelanguage that can be used to program queries (referred to as CQLqueries) that can be executed against event streams. In certainembodiments, CQL is based upon SQL with added constructs that supportprocessing of streaming events data.

In one embodiment, an event processing application may be composed ofthe following component types:

(1) One or more adapters that interface directly to the input and outputstream and relation sources and sinks. Adapters are configured tounderstand the input and output stream protocol, and are responsible forconverting the event data into a normalized form that can be queried byan application processor. Adapters may forward the normalized event datainto channels or output streams and relation sinks. Event adapters maybe defined for a variety of data sources and sinks.(2) One or more channels that act as event processing endpoints. Amongother things, channels are responsible for queuing event data until theevent processing agent can act upon it.(2) One or more application processors (or event processing agents) areconfigured to consume normalized event data from a channel, process itusing queries to select notable events, and forward (or copy) theselected notable events to an output channel.(4) One or more beans are configured to listen to the output channel,and are triggered by the insertion of a new event into the outputchannel. In some embodiments, this user code is a plain-old-Java-object(POJO). The user application can make use of a set of external services,such as JMS, Web services, and file writers, to forward the generatedevents to external event sinks.(5) Event beans may be registered to listen to the output channel, andare triggered by the insertion of a new event into the output channel.In some embodiments, this user code may use the Oracle CEP event beanAPI so that the bean can be managed by Oracle CEP.

In one embodiment, an event adapter provides event data to an inputchannel. The input channel is connected to a CQL processor associatedwith one or more CQL queries that operate on the events offered by theinput channel. The CQL processor is connected to an output channel towhich query results are written.

In some embodiments, an assembly file may be provided for an eventprocessing application describing the various components of the eventprocessing application, how the components are connected together, andevent types processed by the application. Separate files may be providedfor specifying the continuous query or business logic for selection ofevents.

It should be appreciated that system 200 depicted in FIG. 2 may haveother components than those depicted in FIG. 2. Further, the embodimentshown in FIG. 2 is only one example of a system that may incorporate anembodiment of the present disclosure. In some other embodiments, system200 may have more or fewer components than shown in FIG. 2, may combinetwo or more components, or may have a different configuration orarrangement of components. System 200 can be of various types includinga personal computer, a portable device (e.g., a mobile telephone ordevice), a workstation, a network computer, a mainframe, a kiosk, aserver, or any other data processing system. In some other embodiments,system 200 may be configured as a distributed system where one or morecomponents of system 200 are distributed across one or more networks inthe cloud.

The one or more of the components depicted in FIG. 2 may be implementedin software, in hardware, or combinations thereof. In some embodiments,the software may be stored in memory (e.g., a non-transitorycomputer-readable medium), on a memory device, or some other physicalmemory and may be executed by one or more processing units (e.g., one ormore processors, one or more processor cores, one or more GPUs, etc.).

Illustrative methods and systems for implementing the flexible eventingestion framework are described above. Some or all of these systemsand methods may, but need not, be implemented at least partially byarchitectures and processes such as those shown at least in FIGS. 1-2above.

FIG. 3 depicts a simplified diagram of an adapter framework 300 thatincludes at least the following components: a transport component 302, amapper component 304, a trigger component 306, a filter component and/oran extractor component 308, a converter component 310, and a changedetector component 312.

In some examples, the transport component 302 may be responsible forreceiving contents from the source. The contents may include more thanone event. Additionally, the mapper component 304 may be responsible forconverting one input type of content to another type that the systemunderstands and generates events. The mapper component may generate theoutput events directly or create an intermediate java type and use anextractor component. In some example, the Java Architecture for XMLBinding (JAXB) may be used in implementing the mapper component and JAXBmay generates intermediate java classes that can further uses anextractor component to convert to events. In some examples, the triggercomponent 306 may invoke the transport component 302 to receive content(events) from the source. The trigger component 306 allows control ofprocessing source data logic when and what. It can provide an initialset of the source data and it can schedule extraction of data from thesource. In some examples, the adapter only deals with processing data.Thus, it may be desirable to implement a triggerable interface andfollow some protocol to invoke the transport component to receivecontents. Some of examples of embodiments of the trigger components arescheduled trigger, folder monitor trigger, delay loopback trigger, andconsole input trigger. A scheduled trigger may trigger on a scheduleand/or may support “At,” “Delay,” and “Duration.” A folder monitortrigger may monitor folders and send new/updated file paths. A delayloopback trigger may support delay load and/or delay repeatfunctionality. A console input trigger may retrieve input from a consoleand may be useful in demo scenarios.

In some examples, the extractor component 308 may be configured toextract fields the output type of the mapper component. The extractorcomponent 308 may be implemented based at least in part on a dynamicallygenerated extractor class. Having a specific extractor component 308 canenable adapter-specific extraction. The extractor component 308 canprovide simple rules (including “foreach” rules) for extraction and canprovide a mapping of properties (e.g., using a converter). The extractorcomponent 308 may work with general Extensible Stylesheet LanguageTransformation (XSLT) processing. Example rule of 308 includes:

foreach(    AlertEntry:alerts,    ‘*;   geometry=GeomConverter(polygon,AlertGeocode:geocode/   valueNames,AlertGeocode:geocode/values’)That is, for each AlertEntry type in alerts of AlertFeed, the extractorcomponent may copy all properties but polygon, valueNames of geocodeproperty Of AlertGeocodeType, values of geocode property OfAlertGeocodeType passed to GeomConverter which creates a Geometry typeand assign it to geometry

In some examples, the filter component 308 may be configured to filterevents based at least in part on fields of the events. The filtercomponent 308 may be configured to filter based at least in part onevent property. The filter component 308 can support inclusion or caneasily be expanded to general Boolean expression. The filter component308 and the extractor component 308 may be configured as two separatecomponents or as a single component that both extracts and filters.

In some examples, a converter component 310 may be configured to converttypes of fields. For example, property types may be automaticallyconverted for built-in types. Some geometry types may require moretreatment. For example, they may be spread into multiple properties,they may be complex type such as Extensible Markup Language (XML) orJavaScript Object Notation (JSON), and/or they may need geocodehandline. In some examples, a geometry converter may be configured forreceiving weather data or the like. The arguments may include a list ofgeocode names, a list of geocode values, and an optional list oflongitude/latitude pairs. For each geocode name/value, the adapter maydecode the geocode and get polygon data from a geocode database. Then,the geometry converter may return a list of geometries corresponding tothe geocode name/value pairs.

In some examples, a change detector component 312 may be configured todetect changes in contents/events received by the custom adapter. Thechange detector component 312 may detect changes of inputcontents/events and send events of insert/update/delete kinds. In someexamples, the change detector component 312 may only work withRelation-type data; however, in other examples, it may work with alldata types. The change detector component 312 may be useful for workingwith sending updates from the same datasource (e.g., RSS). In someexamples, the Key column from one of fields of tuple is required inorder to detect insert/update/delete kinds. One embodiment of changedetection component is using a hash table datastructure where the oldevents are stored in the hash table and the Key column is to detectinsert/update/delete kinds. Using a map change detection component, thesystem may handle auto expiration from the time specified in the event.

In many examples, systems that process data from a stream may provide anadapter or allow customers to write their own adapter code to be used inthe ingestion system. But, most adapter frameworks don't have many APIs,or they only deal with the transport layer. Meaning, the APIs may onlybe used for instructing the adapter on where to read the data from. Somemore advanced adapters may be configured with APIs for mapping the data.However, the flexible event ingestion framework described herein canallow for APIs that can be configured to execute or control severalother event ingestion components, some of which have been describedabove.

In one example, in order to handle an RSS data source, it may be helpfulto be able to schedule pulling the data and convert the data into aparticular form (e.g., XML). Sometimes, it may be helpful to extract thesome parts of the content into an appropriate event format.Additionally, RSS content may have a timestamp or time mark, which canenable the event ingestion system to determine which data points arerelevant (e.g., it may not be helpful to process data that is outdated).By having this construct, it is possible to mix and match differentcomponents as needed to flexibly configure the adapter framework to meetparticular needs. For example, a Comma Separated Values (CSV) adaptermay read a CSV file and then convert the CSV format to a tuple format.Similarly, for JavaScript Object Notation (JSON) files, a JSON adaptermay read the JSON file and then convert to a tuple format. But, thatbasically involves two parts already because the CSV file is part of thetransport but CSV is more like a mapper area. So, if it's separated outso the file is at the transport, then components can be mixed andmatched for different formats so the transport and mapper are separatedout (e.g., so that the same code doesn't need to be rewritten).Similarly, for the trigger, the trigger may be configured as a mechanismthat triggers the transport (e.g., an HTTP transport) to read something(e.g., an HTTP file) every particular duration. Alternatively, thetrigger may also be configured to monitor the source and identify whenthe file is new, and trigger the transport to read the new file. Thetrigger may also be activated by a user (e.g., selecting a read of aninput source from a console or other UI).

In some examples, the change detector component 312 may be configured asa content change detector may actually be located between the transportcomponent 302 and the mapper component 304. This change detector (e.g.,the content change detector) may identity when data extracted by thetransport component 302 was generated and/or received (e.g., based onits timestamp or other metadata). Another type of change detector (e.g.,a tuple-level change detector), however, may be implemented on top ofeach individual tuple. For example, for each individual tuple, a hashtable may be maintained on top of the tuples. Then, using a key-valuecomparison, the content change detector can identify whether the valueof the tuple has changed for the same ID (key). Further, in someexamples, the trigger component 306 may be configured to trigger thetransport component 302 to read new data based at least in part on achange detected by the change detector 312. The mix-and-matchcapabilities of these components make the adapter more flexible becausenone of the code is built into the adapter. Thus, a trigger component306 written for one particular adapter (e.g., an RSS adapter) may laterbe used within a JSON adapter without having to write new code for theadapter. Instead, an API method call may be made by the adapter toimplement the trigger component 306 regardless of the type of adapterbeing used and/or the type of the data being received from the source.For example, a file adapter may include a JSON mapper. Using that, anincoming JSON file can be written to the system. Later on, if the systemwants to monitor (e.g., every hour) and check if the JSON file haschanged, the adapter configuration and/or application configuration canbe changed to add a scheduled trigger with a content change detector.Thus, the behavior is extended without rewriting the adapter.

FIG. 4 depicts an example 400 set of inputs and outputs to a tupleextraction class or the extractor component 308.

Typically, a programmer writes some code (e.g., in Java or other objectoriented language), including some classes, framework, etc.Additionally, in Java is something called bytecode manipulation, where aprogrammer can create a dynamic class for a virtual machine. Events maybe received as XML code or in Java. After converting the XML portion toJava classes, we may be left with entries of a class (e.g., the lefthand side of the below diagram, where “AlertFeed” and “AlertEntry” arethe classes), and from these classes it is desired to create a tuple,“AlertEntryEvent.” In order to do that, each alert entry from the“AlertFeed” class can be analyzed and extract each field (e.g., event,id, title, etc.) while converting the “AlertGeocode” class into the“geometry” format. Essentially, the extractor reads from one event type,and then creates a new event type. Essentially, taking the Java classpseudocode and converting it into tuples.

foreach( AlertEntry:alerts, ‘*;geometry=GeomConverter(polygon,AlertGeocode:geocode/valueNames,AlertGeocode:geocode/values’)

For each input event, a field (property) from each event is extracted,and the type is converted to the type of the output event field(property), and then set the property to the output event.

Extractor

-   -   Adapter specific extraction    -   Provides Very Simple Rule        -   Foreach        -   Mapping of properties            -   Use converter            -   Also works with general XSLT processing        -   XSLT processing is also added    -   foreach(        -   AlertEntry: alerts,        -   ‘*;        -   geometry=GeomConverter(polygon,AlertGeocode:geocode/valueNames,AlertGeocode:g            eocode/values')        -   For each AlertEntry type in alerts of AlertFeed        -   copy all properties        -   but polygon, valueNames of geocode property Of            AlertGeocodeType, values of geocode property Of            AlertGeocodeType passed to GeomConverter which creates a            Geometry type and assign it to geometry            Extractor Optimization    -   Foreach input events        -   1. Extract fields from input event        -   2. Convert type to output event field        -   3. Set to output event        -   4. Extract fields and converting type operation is performed            for each fields->bottleneck of performance        -   5. Optimize Extract Field        -   6. Looping of field can be removed by loop unrolling            Typical Field Extractors

Converting input field to integer value (e.g., output field type isinteger)

public int ExtractField1(Object v)

{  If (v instance of Integer) return ((Integer)v);  else If (v instanceof Number) return ((Number)v).intValue( );  else if (v instance ofString) return Integer.parseInt((String)v)  else newRuntimeException(“failed to convert”) }

The adapter framework needs to handle generic input event type. Do notknow the input field types before runtime, so doing many type checkingfor every possible cases.

Optimized Field Extractor

public final int ExtractField1Int(String v)

{  return Integer.parseInt(v); }

-   -   After the first extraction, we know the first field is String        type and we are converting String to Integer.        -   We can omit type checking and other if clauses        -   We can optimize further by inlining the function directly,            but Java JIT will also convert the methods with ‘final’ to            inline functions            Optimized Extractor            public class ExtractorXX

{  EventType inputEvent, outputEvent;  EventProperty inputField1,inputField2, ...;  EventProperty outputField1, outputField2, ...; //Field extractors  public int ExtractField1Int(Object v) { }  publicString ExtractField2String(Object v) { }  ...public Object extract(Object event)

{  Object outputEvent = outputEventType.createEvent( ); outputField1.set(outputEvent,ExtractField1Int(inputField1.get(event))); outputField2.set(outputEvent, ExtractField2String(inputField2. get(event)));  ...  return outputEvent; } }

FIG. 5 is a flow diagram of a process for implementing a flexible eventingestion framework within an event processing system in accordance withat least one embodiment. This process is illustrated as a logical flowdiagram, each operation of which represents a sequence of operationsthat can be implemented in hardware, computer instructions, or acombination thereof. In the context of computer instructions, theoperations represent computer-executable instructions stored on one ormore computer-readable storage media that, when executed by one or moreprocessors, perform the recited operations. Generally, computerexecutable instructions include routines, programs, objects, components,data structures and the like that perform particular functions orimplement particular data types. The order in which the operations aredescribed is not intended to be construed as a limitation, and anynumber of the described operations can be combined in any order and/orin parallel to implement the processes.

Additionally, some, any, or all of the process (or any other processesdescribed herein, or variations and/or combinations thereof) may beperformed under the control of one or more computer systems configuredwith executable instructions and may be implemented as code (e.g.,executable instructions, one or more computer programs or one or moreapplications) executing collectively on one or more processors, byhardware or combinations thereof. As noted above, the code may be storedon a computer-readable storage medium, for example, in the form of acomputer program comprising a plurality of instructions executable byone or more processors. The computer-readable storage medium may benon-transitory.

In some examples, the one or more service provider computers 106 (e.g.,utilizing at least the event ingestion module 148 shown in FIG. 1 mayperform the process 500 of FIG. 5. In FIG. 5 the process 500 may includeidentifying an input stream of a plurality of events at 502. At 504, theprocess 500 may include implementing an adapter (e.g., an adapterframework) for ingesting the plurality of events of the input stream.The adapter may be configured with a transport component and/or a mappercomponent. The transport component may be configured to receive theevents from the source and the mapper component may be configured toconvert one input type to another input type. At 506, the process 500may include receiving at least one additional component for modifyingthe adapter. The additional components may be received form programmers,system administrators, and/or other adapter frameworks. The additionalcomponents may be configured in such a way to be plugged into theadapter framework using any known techniques. The process 500 may alsoinclude modifying the adapter by implementing the additional componentwith the already implemented transport and mapper components at 508. At510, the process 500 may include generating a tuple for at least thefirst event of the event stream based at least in part on the modifiedadapter. At 512, the process 500 may end by providing the tuple to anevent processor.

FIG. 6 depicts a simplified diagram of a distributed system 600 forimplementing one of the embodiments. In the illustrated embodiment,distributed system 600 includes one or more client computing devices602, 604, 606, and 608, which are configured to execute and operate aclient application such as a web browser, proprietary client (e.g.,Oracle Forms), or the like over one or more network(s) 610. Server 612may be communicatively coupled with remote client computing devices 602,604, 606, and 608 via network 610.

In various embodiments, server 612 may be adapted to run one or moreservices or software applications provided by one or more of thecomponents of the system. The services or software applications caninclude non-virtual and virtual environments. Virtual environments caninclude those used for virtual events, tradeshows, simulators,classrooms, shopping exchanges, and enterprises, whether two- orthree-dimensional (3D) representations, page-based logical environments,or otherwise. In some embodiments, these services may be offered asweb-based or cloud services or under a Software as a Service (SaaS)model to the users of client computing devices 602, 604, 606, and/or608. Users operating client computing devices 602, 604, 606, and/or 608may in turn utilize one or more client applications to interact withserver 612 to utilize the services provided by these components.

In the configuration depicted in the figure, the software components618, 620 and 622 of system 600 are shown as being implemented on server612. In other embodiments, one or more of the components of system 600and/or the services provided by these components may also be implementedby one or more of the client computing devices 602, 604, 606, and/or608. Users operating the client computing devices may then utilize oneor more client applications to use the services provided by thesecomponents. These components may be implemented in hardware, firmware,software, or combinations thereof. It should be appreciated that variousdifferent system configurations are possible, which may be differentfrom distributed system 600. The embodiment shown in the figure is thusone example of a distributed system for implementing an embodimentsystem and is not intended to be limiting.

Client computing devices 602, 604, 606, and/or 608 may be portablehandheld devices (e.g., an iPhone®, cellular telephone, an iPad®,computing tablet, a personal digital assistant (PDA)) or wearabledevices (e.g., a Google Glass® head mounted display), running softwaresuch as Microsoft Windows Mobile®, and/or a variety of mobile operatingsystems such as iOS, Windows Phone, Android, BlackBerry 8, Palm OS, andthe like, and being Internet, e-mail, short message service (SMS),Blackberry®, or other communication protocol enabled. The clientcomputing devices can be general purpose personal computers including,by way of example, personal computers and/or laptop computers runningvarious versions of Microsoft Windows®, Apple Macintosh®, and/or Linuxoperating systems. The client computing devices can be workstationcomputers running any of a variety of commercially-available UNIX® orUNIX-like operating systems, including without limitation the variety ofGNU/Linux operating systems, such as for example, Google Chrome OS.Alternatively, or in addition, client computing devices 602, 604, 606,and 608 may be any other electronic device, such as a thin-clientcomputer, an Internet-enabled gaming system (e.g., a Microsoft Xboxgaming console with or without a Kinect® gesture input device), and/or apersonal messaging device, capable of communicating over network(s) 610.

Although exemplary distributed system 600 is shown with four clientcomputing devices, any number of client computing devices may besupported. Other devices, such as devices with sensors, etc., mayinteract with server 612.

Network(s) 610 in distributed system 600 may be any type of networkfamiliar to those skilled in the art that can support datacommunications using any of a variety of commercially-availableprotocols, including without limitation TCP/IP (transmission controlprotocol/Internet protocol), SNA (systems network architecture), IPX(Internet packet exchange), AppleTalk, and the like. Merely by way ofexample, network(s) 610 can be a local area network (LAN), such as onebased on Ethernet, Token-Ring and/or the like. Network(s) 610 can be awide-area network and the Internet. It can include a virtual network,including without limitation a virtual private network (VPN), anintranet, an extranet, a public switched telephone network (PSTN), aninfra-red network, a wireless network (e.g., a network operating underany of the Institute of Electrical and Electronics (IEEE) 602.11 suiteof protocols, Bluetooth®, and/or any other wireless protocol); and/orany combination of these and/or other networks.

Server 612 may be composed of one or more general purpose computers,specialized server computers (including, by way of example, PC (personalcomputer) servers, UNIX® servers, mid-range servers, mainframecomputers, rack-mounted servers, etc.), server farms, server clusters,or any other appropriate arrangement and/or combination. Server 612 caninclude one or more virtual machines running virtual operating systems,or other computing architectures involving virtualization. One or moreflexible pools of logical storage devices can be virtualized to maintainvirtual storage devices for the server. Virtual networks can becontrolled by server 612 using software defined networking. In variousembodiments, server 612 may be adapted to run one or more services orsoftware applications described in the foregoing disclosure. Forexample, server 612 may correspond to a server for performing processingdescribed above according to an embodiment of the present disclosure.

Server 612 may run an operating system including any of those discussedabove, as well as any commercially available server operating system.Server 612 may also run any of a variety of additional serverapplications and/or mid-tier applications, including HTTP (hypertexttransport protocol) servers, FTP (file transfer protocol) servers, CGI(common gateway interface) servers, JAVA® servers, database servers, andthe like. Exemplary database servers include without limitation thosecommercially available from Oracle, Microsoft, Sybase, IBM(International Business Machines), and the like.

In some implementations, server 612 may include one or more applicationsto analyze and consolidate data feeds and/or event updates received fromusers of client computing devices 602, 604, 606, and 608. As an example,data feeds and/or event updates may include, but are not limited to,Twitter® feeds, Facebook® updates or real-time updates received from oneor more third party information sources and continuous data streams,which may include real-time events related to sensor data applications,financial tickers, network performance measuring tools (e.g., networkmonitoring and traffic management applications), clickstream analysistools, automobile traffic monitoring, and the like. Server 612 may alsoinclude one or more applications to display the data feeds and/orreal-time events via one or more display devices of client computingdevices 602, 604, 606, and 608.

Distributed system 600 may also include one or more databases 614 and616. Databases 614 and 616 may reside in a variety of locations. By wayof example, one or more of databases 614 and 616 may reside on anon-transitory storage medium local to (and/or resident in) server 612.Alternatively, databases 614 and 616 may be remote from server 612 andin communication with server 612 via a network-based or dedicatedconnection. In one set of embodiments, databases 614 and 616 may residein a storage-area network (SAN). Similarly, any necessary files forperforming the functions attributed to server 612 may be stored locallyon server 612 and/or remotely, as appropriate. In one set ofembodiments, databases 614 and 616 may include relational databases,such as databases provided by Oracle, that are adapted to store, update,and retrieve data in response to SQL-formatted commands.

FIG. 7 is a simplified block diagram of one or more components of asystem environment 700 by which services provided by one or morecomponents of an embodiment system may be offered as cloud services, inaccordance with an embodiment of the present disclosure. In theillustrated embodiment, system environment 700 includes one or moreclient computing devices 704, 706, and 708 that may be used by users tointeract with a cloud infrastructure system 702 that provides cloudservices. The client computing devices may be configured to operate aclient application such as a web browser, a proprietary clientapplication (e.g., Oracle Forms), or some other application, which maybe used by a user of the client computing device to interact with cloudinfrastructure system 702 to use services provided by cloudinfrastructure system 702.

It should be appreciated that cloud infrastructure system 702 depictedin the figure may have other components than those depicted. Further,the embodiment shown in the figure is only one example of a cloudinfrastructure system that may incorporate an embodiment of thedisclosure. In some other embodiments, cloud infrastructure system 702may have more or fewer components than shown in the figure, may combinetwo or more components, or may have a different configuration orarrangement of components.

Client computing devices 704, 706, and 708 may be devices similar tothose described above for 602, 604, 606, and 608.

Although exemplary system environment 700 is shown with three clientcomputing devices, any number of client computing devices may besupported. Other devices such as devices with sensors, etc. may interactwith cloud infrastructure system 702.

Network(s) 710 may facilitate communications and exchange of databetween clients 704, 706, and 708 and cloud infrastructure system 702.Each network may be any type of network familiar to those skilled in theart that can support data communications using any of a variety ofcommercially-available protocols, including those described above fornetwork(s) 610.

Cloud infrastructure system 702 may comprise one or more computersand/or servers that may include those described above for server 612.

In certain embodiments, services provided by the cloud infrastructuresystem may include a host of services that are made available to usersof the cloud infrastructure system on demand, such as online datastorage and backup solutions, Web-based e-mail services, hosted officesuites and document collaboration services, database processing, managedtechnical support services, and the like. Services provided by the cloudinfrastructure system can dynamically scale to meet the needs of itsusers. A specific instantiation of a service provided by cloudinfrastructure system is referred to herein as a “service instance.” Ingeneral, any service made available to a user via a communicationnetwork, such as the Internet, from a cloud service provider's system isreferred to as a “cloud service.” Typically, in a public cloudenvironment, servers and systems that make up the cloud serviceprovider's system are different from the customer's own on-premisesservers and systems. For example, a cloud service provider's system mayhost an application, and a user may, via a communication network such asthe Internet, on demand, order and use the application.

In some examples, a service in a computer network cloud infrastructuremay include protected computer network access to storage, a hosteddatabase, a hosted web server, a software application, or other serviceprovided by a cloud vendor to a user, or as otherwise known in the art.For example, a service can include password-protected access to remotestorage on the cloud through the Internet. As another example, a servicecan include a web service-based hosted relational database and ascript-language middleware engine for private use by a networkeddeveloper. As another example, a service can include access to an emailsoftware application hosted on a cloud vendor's web site.

In certain embodiments, cloud infrastructure system 702 may include asuite of applications, middleware, and database service offerings thatare delivered to a customer in a self-service, subscription-based,elastically scalable, reliable, highly available, and secure manner. Anexample of such a cloud infrastructure system is the Oracle Public Cloudprovided by the present assignee.

‘Big data’ can be hosted and/or manipulated by the infrastructure systemon many levels and at different scales. Extremely large data sets can bestored and manipulated by analysts and researchers to visualize largeamounts of data, detect trends, and/or otherwise interact with the data.Tens, hundreds, or thousands of processors linked in parallel can actupon such data in order to present it or simulate external forces on thedata or what it represents. These data sets can involve structured data,such as that organized in a database or otherwise according to astructured model, and/or unstructured data (e.g., emails, images, datablobs (binary large objects), web pages, complex event processing). Byleveraging an ability of an embodiment to relatively quickly focus more(or fewer) computing resources upon an objective, the cloudinfrastructure system may be better available to carry out tasks onlarge data sets based on demand from a business, government agency,research organization, private individual, group of like-mindedindividuals or organizations, or other entity.

In various embodiments, cloud infrastructure system 702 may be adaptedto automatically provision, manage and track a customer's subscriptionto services offered by cloud infrastructure system 702. Cloudinfrastructure system 702 may provide the cloud services via differentdeployment models. For example, services may be provided under a publiccloud model in which cloud infrastructure system 702 is owned by anorganization selling cloud services (e.g., owned by Oracle) and theservices are made available to the general public or different industryenterprises. As another example, services may be provided under aprivate cloud model in which cloud infrastructure system 702 is operatedsolely for a single organization and may provide services for one ormore entities within the organization. The cloud services may also beprovided under a community cloud model in which cloud infrastructuresystem 702 and the services provided by cloud infrastructure system 702are shared by several organizations in a related community. The cloudservices may also be provided under a hybrid cloud model, which is acombination of two or more different models.

In some embodiments, the services provided by cloud infrastructuresystem 702 may include one or more services provided under Software as aService (SaaS) category, Platform as a Service (PaaS) category,Infrastructure as a Service (IaaS) category, or other categories ofservices including hybrid services. A customer, via a subscriptionorder, may order one or more services provided by cloud infrastructuresystem 702. Cloud infrastructure system 702 then performs processing toprovide the services in the customer's subscription order.

In some embodiments, the services provided by cloud infrastructuresystem 702 may include, without limitation, application services,platform services and infrastructure services. In some examples,application services may be provided by the cloud infrastructure systemvia a SaaS platform. The SaaS platform may be configured to providecloud services that fall under the SaaS category. For example, the SaaSplatform may provide capabilities to build and deliver a suite ofon-demand applications on an integrated development and deploymentplatform. The SaaS platform may manage and control the underlyingsoftware and infrastructure for providing the SaaS services. Byutilizing the services provided by the SaaS platform, customers canutilize applications executing on the cloud infrastructure system.Customers can acquire the application services without the need forcustomers to purchase separate licenses and support. Various differentSaaS services may be provided. Examples include, without limitation,services that provide solutions for sales performance management,enterprise integration, and business flexibility for largeorganizations.

In some embodiments, platform services may be provided by the cloudinfrastructure system via a PaaS platform. The PaaS platform may beconfigured to provide cloud services that fall under the PaaS category.Examples of platform services may include without limitation servicesthat enable organizations (such as Oracle) to consolidate existingapplications on a shared, common architecture, as well as the ability tobuild new applications that leverage the shared services provided by theplatform. The PaaS platform may manage and control the underlyingsoftware and infrastructure for providing the PaaS services. Customerscan acquire the PaaS services provided by the cloud infrastructuresystem without the need for customers to purchase separate licenses andsupport. Examples of platform services include, without limitation,Oracle Java Cloud Service (JCS), Oracle Database Cloud Service (DBCS),and others.

By utilizing the services provided by the PaaS platform, customers canemploy programming languages and tools supported by the cloudinfrastructure system and also control the deployed services. In someembodiments, platform services provided by the cloud infrastructuresystem may include database cloud services, middleware cloud services(e.g., Oracle Fusion Middleware services), and Java cloud services. Inone embodiment, database cloud services may support shared servicedeployment models that enable organizations to pool database resourcesand offer customers a Database as a Service in the form of a databasecloud. Middleware cloud services may provide a platform for customers todevelop and deploy various business applications, and Java cloudservices may provide a platform for customers to deploy Javaapplications, in the cloud infrastructure system.

Various different infrastructure services may be provided by an IaaSplatform in the cloud infrastructure system. The infrastructure servicesfacilitate the management and control of the underlying computingresources, such as storage, networks, and other fundamental computingresources for customers utilizing services provided by the SaaS platformand the PaaS platform.

In certain embodiments, cloud infrastructure system 702 may also includeinfrastructure resources 730 for providing the resources used to providevarious services to customers of the cloud infrastructure system. In oneembodiment, infrastructure resources 730 may include pre-integrated andoptimized combinations of hardware, such as servers, storage, andnetworking resources to execute the services provided by the PaaSplatform and the SaaS platform.

In some embodiments, resources in cloud infrastructure system 702 may beshared by multiple users and dynamically re-allocated per demand.Additionally, resources may be allocated to users in different timezones. For example, cloud infrastructure system 730 may enable a firstset of users in a first time zone to utilize resources of the cloudinfrastructure system for a specified number of hours and then enablethe re-allocation of the same resources to another set of users locatedin a different time zone, thereby maximizing the utilization ofresources.

In certain embodiments, a number of internal shared services 732 may beprovided that are shared by different components or modules of cloudinfrastructure system 702 and by the services provided by cloudinfrastructure system 702. These internal shared services may include,without limitation, a security and identity service, an integrationservice, an enterprise repository service, an enterprise managerservice, a virus scanning and white list service, a high availability,backup and recovery service, service for enabling cloud support, anemail service, a notification service, a file transfer service, and thelike.

In certain embodiments, cloud infrastructure system 702 may providecomprehensive management of cloud services (e.g., SaaS, PaaS, and IaaSservices) in the cloud infrastructure system. In one embodiment, cloudmanagement functionality may include capabilities for provisioning,managing and tracking a customer's subscription received by cloudinfrastructure system 702, and the like.

In one embodiment, as depicted in the figure, cloud managementfunctionality may be provided by one or more modules, such as an ordermanagement module 720, an order orchestration module 722, an orderprovisioning module 724, an order management and monitoring module 726,and an identity management module 728. These modules may include or beprovided using one or more computers and/or servers, which may begeneral purpose computers, specialized server computers, server farms,server clusters, or any other appropriate arrangement and/orcombination.

In exemplary operation 734, a customer using a client device, such asclient device 704, 706 or 708, may interact with cloud infrastructuresystem 702 by requesting one or more services provided by cloudinfrastructure system 702 and placing an order for a subscription forone or more services offered by cloud infrastructure system 702. Incertain embodiments, the customer may access a cloud User Interface(UI), cloud UI 712, cloud UI 714 and/or cloud UI 716 and place asubscription order via these UIs. The order information received bycloud infrastructure system 702 in response to the customer placing anorder may include information identifying the customer and one or moreservices offered by the cloud infrastructure system 702 that thecustomer intends to subscribe to.

After an order has been placed by the customer, the order information isreceived via the cloud UIs, 712, 714 and/or 716.

At operation 736, the order is stored in order database 718. Orderdatabase 718 can be one of several databases operated by cloudinfrastructure system 718 and operated in conjunction with other systemelements.

At operation 738, the order information is forwarded to an ordermanagement module 720. In some instances, order management module 720may be configured to perform billing and accounting functions related tothe order, such as verifying the order, and upon verification, bookingthe order.

At operation 740, information regarding the order is communicated to anorder orchestration module 722. Order orchestration module 722 mayutilize the order information to orchestrate the provisioning ofservices and resources for the order placed by the customer. In someinstances, order orchestration module 722 may orchestrate theprovisioning of resources to support the subscribed services using theservices of order provisioning module 724.

In certain embodiments, order orchestration module 722 enables themanagement of business processes associated with each order and appliesbusiness logic to determine whether an order should proceed toprovisioning. At operation 742, upon receiving an order for a newsubscription, order orchestration module 722 sends a request to orderprovisioning module 724 to allocate resources and configure thoseresources needed to fulfill the subscription order. Order provisioningmodule 724 enables the allocation of resources for the services orderedby the customer. Order provisioning module 724 provides a level ofabstraction between the cloud services provided by cloud infrastructuresystem 700 and the physical implementation layer that is used toprovision the resources for providing the requested services. Orderorchestration module 722 may thus be isolated from implementationdetails, such as whether or not services and resources are actuallyprovisioned on the fly or pre-provisioned and only allocated/assignedupon request.

At operation 744, once the services and resources are provisioned, anotification of the provided service may be sent to customers on clientdevices 704, 706 and/or 708 by order provisioning module 724 of cloudinfrastructure system 702.

At operation 746, the customer's subscription order may be managed andtracked by an order management and monitoring module 726. In someinstances, order management and monitoring module 726 may be configuredto collect usage statistics for the services in the subscription order,such as the amount of storage used, the amount data transferred, thenumber of users, and the amount of system up time and system down time.

In certain embodiments, cloud infrastructure system 700 may include anidentity management module 728. Identity management module 728 may beconfigured to provide identity services, such as access management andauthorization services in cloud infrastructure system 700. In someembodiments, identity management module 728 may control informationabout customers who wish to utilize the services provided by cloudinfrastructure system 702. Such information can include information thatauthenticates the identities of such customers and information thatdescribes which actions those customers are authorized to performrelative to various system resources (e.g., files, directories,applications, communication ports, memory segments, etc.) Identitymanagement module 728 may also include the management of descriptiveinformation about each customer and about how and by whom thatdescriptive information can be accessed and modified.

FIG. 8 illustrates an exemplary computer system 800, in which variousembodiments of the present disclosure may be implemented. The system 800may be used to implement any of the computer systems described above. Asshown in the figure, computer system 800 includes a processing unit 804that communicates with a number of peripheral subsystems via a bussubsystem 802. These peripheral subsystems may include a processingacceleration unit 806, an I/O subsystem 808, a storage subsystem 818 anda communications subsystem 824. Storage subsystem 818 includes tangiblecomputer-readable storage media 822 and a system memory 810.

Bus subsystem 802 provides a mechanism for letting the variouscomponents and subsystems of computer system 800 communicate with eachother as intended. Although bus subsystem 802 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 802 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Forexample, such architectures may include an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard.

Processing unit 804, which can be implemented as one or more integratedcircuits (e.g., a conventional microprocessor or microcontroller),controls the operation of computer system 800. One or more processorsmay be included in processing unit 804. These processors may includesingle core or multicore processors. In certain embodiments, processingunit 804 may be implemented as one or more independent processing units832 and/or 834 with single or multicore processors included in eachprocessing unit. In other embodiments, processing unit 804 may also beimplemented as a quad-core processing unit formed by integrating twodual-core processors into a single chip.

In various embodiments, processing unit 804 can execute a variety ofprograms in response to program code and can maintain multipleconcurrently executing programs or processes. At any given time, some orall of the program code to be executed can be resident in processor(s)804 and/or in storage subsystem 818. Through suitable programming,processor(s) 804 can provide various functionalities described above.Computer system 800 may additionally include a processing accelerationunit 806, which can include a digital signal processor (DSP), aspecial-purpose processor, and/or the like.

I/O subsystem 808 may include user interface input devices and userinterface output devices. User interface input devices may include akeyboard, pointing devices such as a mouse or trackball, a touchpad ortouch screen incorporated into a display, a scroll wheel, a click wheel,a dial, a button, a switch, a keypad, audio input devices with voicecommand recognition systems, microphones, and other types of inputdevices. User interface input devices may include, for example, motionsensing and/or gesture recognition devices such as the Microsoft Kinect®motion sensor that enables users to control and interact with an inputdevice, such as the Microsoft Xbox® 360 game controller, through anatural user interface using gestures and spoken commands. Userinterface input devices may also include eye gesture recognition devicessuch as the Google Glass® blink detector that detects eye activity(e.g., ‘blinking’ while taking pictures and/or making a menu selection)from users and transforms the eye gestures as input into an input device(e.g., Google Glass®). Additionally, user interface input devices mayinclude voice recognition sensing devices that enable users to interactwith voice recognition systems (e.g., Siri® navigator), through voicecommands.

User interface input devices may also include, without limitation, threedimensional (3D) mice, joysticks or pointing sticks, gamepads andgraphic tablets, and audio/visual devices such as speakers, digitalcameras, digital camcorders, portable media players, webcams, imagescanners, fingerprint scanners, barcode reader 3D scanners, 3D printers,laser rangefinders, and eye gaze tracking devices. Additionally, userinterface input devices may include, for example, medical imaging inputdevices such as computed tomography, magnetic resonance imaging,position emission tomography, medical ultrasonography devices. Userinterface input devices may also include, for example, audio inputdevices such as MIDI keyboards, digital musical instruments and thelike.

User interface output devices may include a display subsystem, indicatorlights, or non-visual displays such as audio output devices, etc. Thedisplay subsystem may be a cathode ray tube (CRT), a flat-panel device,such as that using a liquid crystal display (LCD) or plasma display, aprojection device, a touch screen, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system800 to a user or other computer. For example, user interface outputdevices may include, without limitation, a variety of display devicesthat visually convey text, graphics and audio/video information such asmonitors, printers, speakers, headphones, automotive navigation systems,plotters, voice output devices, and modems.

Computer system 800 may comprise a storage subsystem 818 that comprisessoftware elements, shown as being currently located within a systemmemory 810. System memory 810 may store program instructions that areloadable and executable on processing unit 804, as well as datagenerated during the execution of these programs.

Depending on the configuration and type of computer system 800, systemmemory 810 may be volatile (such as random access memory (RAM)) and/ornon-volatile (such as read-only memory (ROM), flash memory, etc.) TheRAM typically contains data and/or program modules that are immediatelyaccessible to and/or presently being operated and executed by processingunit 804. In some implementations, system memory 810 may includemultiple different types of memory, such as static random access memory(SRAM) or dynamic random access memory (DRAM). In some implementations,a basic input/output system (BIOS), containing the basic routines thathelp to transfer information between elements within computer system800, such as during start-up, may typically be stored in the ROM. By wayof example, and not limitation, system memory 810 also illustratesapplication programs 812, which may include client applications, Webbrowsers, mid-tier applications, relational database management systems(RDBMS), etc., program data 814, and an operating system 816. By way ofexample, operating system 816 may include various versions of MicrosoftWindows®, Apple Macintosh®, and/or Linux operating systems, a variety ofcommercially-available UNIX® or UNIX-like operating systems (includingwithout limitation the variety of GNU/Linux operating systems, theGoogle Chrome® OS, and the like) and/or mobile operating systems such asiOS, Windows® Phone, Android® OS, BlackBerry® 8 OS, and Palm® OSoperating systems.

Storage subsystem 818 may also provide a tangible computer-readablestorage medium for storing the basic programming and data constructsthat provide the functionality of some embodiments. Software (programs,code modules, instructions) that when executed by a processor providethe functionality described above may be stored in storage subsystem818. These software modules or instructions may be executed byprocessing unit 804. Storage subsystem 818 may also provide a repositoryfor storing data used in accordance with the present disclosure.

Storage subsystem 800 may also include a computer-readable storage mediareader 820 that can further be connected to computer-readable storagemedia 822. Together and, optionally, in combination with system memory810, computer-readable storage media 822 may comprehensively representremote, local, fixed, and/or removable storage devices plus storagemedia for temporarily and/or more permanently containing, storing,transmitting, and retrieving computer-readable information.

Computer-readable storage media 822 containing code, or portions ofcode, can also include any appropriate media known or used in the art,including storage media and communication media, such as but not limitedto, volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information. This can include tangible, non-transitorycomputer-readable storage media such as RAM, ROM, electronicallyerasable programmable ROM (EEPROM), flash memory or other memorytechnology, CD-ROM, digital versatile disk (DVD), or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or other tangible computer readablemedia. When specified, this can also include nontangible, transitorycomputer-readable media, such as data signals, data transmissions, orany other medium which can be used to transmit the desired informationand which can be accessed by computing system 800.

By way of example, computer-readable storage media 822 may include ahard disk drive that reads from or writes to non-removable, nonvolatilemagnetic media, a magnetic disk drive that reads from or writes to aremovable, nonvolatile magnetic disk, and an optical disk drive thatreads from or writes to a removable, nonvolatile optical disk such as aCD ROM, DVD, and Blu-Ray® disk, or other optical media.Computer-readable storage media 822 may include, but is not limited to,Zip® drives, flash memory cards, universal serial bus (USB) flashdrives, secure digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 822 may also include,solid-state drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.The disk drives and their associated computer-readable media may providenon-volatile storage of computer-readable instructions, data structures,program modules, and other data for computer system 800.

Communications subsystem 824 provides an interface to other computersystems and networks. Communications subsystem 824 serves as aninterface for receiving data from and transmitting data to other systemsfrom computer system 800. For example, communications subsystem 824 mayenable computer system 800 to connect to one or more devices via theInternet. In some embodiments communications subsystem 824 can includeradio frequency (RF) transceiver components for accessing wireless voiceand/or data networks (e.g., using cellular telephone technology,advanced data network technology, such as 3G, 4G or EDGE (enhanced datarates for global evolution), WiFi (IEEE 602.11 family standards, orother mobile communication technologies, or any combination thereof),global positioning system (GPS) receiver components, and/or othercomponents. In some embodiments communications subsystem 824 can providewired network connectivity (e.g., Ethernet) in addition to or instead ofa wireless interface.

In some embodiments, communications subsystem 824 may also receive inputcommunication in the form of structured and/or unstructured data feeds826, event streams 828, event updates 830, and the like on behalf of oneor more users who may use computer system 800.

By way of example, communications subsystem 824 may be configured toreceive data feeds 826 in real-time from users of social media networksand/or other communication services such as Twitter® feeds, Facebook®updates, web feeds such as Rich Site Summary (RSS) feeds, and/orreal-time updates from one or more third party information sources.

Additionally, communications subsystem 824 may also be configured toreceive data in the form of continuous data streams, which may includeevent streams 828 of real-time events and/or event updates 830, that maybe continuous or unbounded in nature with no explicit end. Examples ofapplications that generate continuous data may include, for example,sensor data applications, financial tickers, network performancemeasuring tools (e.g. network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like.

Communications subsystem 824 may also be configured to output thestructured and/or unstructured data feeds 826, event streams 828, eventupdates 830, and the like to one or more databases that may be incommunication with one or more streaming data source computers coupledto computer system 800.

Computer system 800 can be one of various types, including a handheldportable device (e.g., an iPhone® cellular phone, an iPad® computingtablet, a PDA), a wearable device (e.g., a Google Glass® head mounteddisplay), a PC, a workstation, a mainframe, a kiosk, a server rack, orany other data processing system.

Due to the ever-changing nature of computers and networks, thedescription of computer system 800 depicted in the figure is intendedonly as a specific example. Many other configurations having more orfewer components than the system depicted in the figure are possible.For example, customized hardware might also be used and/or particularelements might be implemented in hardware, firmware, software (includingapplets), or a combination. Further, connection to other computingdevices, such as network input/output devices, may be employed. Based onthe disclosure and teachings provided herein, a person of ordinary skillin the art will appreciate other ways and/or methods to implement thevarious embodiments.

In the foregoing specification, aspects of the disclosure are describedwith reference to specific embodiments thereof, but those skilled in theart will recognize that the disclosure is not limited thereto. Variousfeatures and aspects of the above-described disclosure may be usedindividually or jointly. Further, embodiments can be utilized in anynumber of environments and applications beyond those described hereinwithout departing from the broader spirit and scope of thespecification. The specification and drawings are, accordingly, to beregarded as illustrative rather than restrictive.

What is claimed is:
 1. A method, comprising: identifying an input sourcecomprising information identifying a plurality of events; implementingan adapter for ingesting the information, the adapter comprising: atransport component that receives the information from the input source;and a mapper component that converts a first input type of a first eventextracted from the input source into a second input type; receiving,from a second adapter different from the adapter implemented foringesting the information, at least one additional component formodifying the adapter, the at least one additional component comprisingat least one of a trigger component, an extractor component, a filtercomponent, a converter component, or a change detector component, andthe second adapter comprising a built-in adapter of an event processingsystem configured to at least one of ingest the information or ingest adifferent set of events from the information; modifying the adapter byimplementing the at least one additional component with the transportcomponent and the mapper component as part of ingesting the information;generating a tuple for at least the first event based at least in parton the modified adapter; and providing the tuple to an event server. 2.The method of claim 1, further comprising enabling creation of the atleast one additional component to customize the adapter for a particularinput stream.
 3. The method of claim 1, wherein the at least oneadditional component comprises a plurality of additional components, andwherein the adapter is modified to implement at least a subset of theplurality of additional components along with the transport componentand the mapper component.
 4. The method of claim 1, wherein the triggercomponent invokes the transport component to extract the first eventfrom the information based at least in part on a schedule or anoccurrence.
 5. The method of claim 1, wherein the extractor componentextracts a field from the first event.
 6. The method of claim 1, whereinthe filter component filters the first event based at least in part on afield of the first event.
 7. The method of claim 1, wherein theconverter component converts a type of the first event to a second type.8. The method of claim 1, wherein the change detector component detectsa change of content of the first event from a previous content of aprevious event associated with the first event.
 9. The method of claim8, wherein the change detector component comprises at least one of acontent level change detector component or a tuple-level change detectorcomponent.
 10. A non-transitory computer-readable medium storingcomputer-executable instructions that, when executed by one or moreprocessors, configures one or more computer systems to perform at least:instructions that cause the one or more processors to implement anadapter for ingesting information that identifies a plurality of eventsof a source document, the adapter comprising: a transport component thatreceives at least a first event of the plurality of events of the sourcedocument; and a mapper component that converts a first input type of thefirst event into a second input type; instructions that cause the one ormore processors to receive, from a second adapter different from theadapter implemented for ingesting the information, at least oneadditional component for modifying the adapter, the at least oneadditional component comprising at least one of a trigger component, anextractor component, a filter component, a converter component, or achange detector component, and the second adapter comprising a built-inadapter of an event processing system configured to at least one ofingest the information or ingest a different set of events from theinformation; instructions that cause the one or more processors tomodify the adapter by implementing the at least one additional componentwith the transport component and the mapper component as part ofingesting the information of the source document; instructions thatcause the one or more processors to execute the modified adapter togenerate a tuple for at least the first event; and instructions thatcause the one or more processors to provide the tuple to an eventserver.
 11. The non-transitory computer-readable medium of claim 10,further comprising instructions that cause the one or more processors toenable creation of the additional component to customize the adapter fora particular input source.
 12. The non-transitory computer-readablemedium of claim 10, wherein the trigger component comprises at least oneof a scheduled trigger, a monitoring trigger, a loop back trigger, or aninput trigger.
 13. The non-transitory computer-readable medium of claim10, wherein the converter component converts geometry-type events.
 14. Asystem, comprising: a memory storing a plurality of instructions; and aprocessor configured to access the memory, the processor furtherconfigured to execute the plurality of instructions to at least:identify an input source comprising information that identifies aplurality of events; implement an adapter for ingesting the informationof the input source, the adapter comprising: a transport component thatreceives at least a first event of the plurality of events of the inputsource; and a mapper component that converts a first input type of thefirst event into a second input type; receive, from a second adapterdifferent from the adapter implemented for ingesting the information, atleast one additional component for modifying the adapter, the at leastone additional component comprising at least one of a trigger component,an extractor component, a filter component, a converter component, or achange detector component, and the second adapter comprising a built-inadapter of an event processing system configured to at least one ofingest the information or ingest a different set of events from theinformation; modify the adapter by implementing the at least oneadditional component with the transport component and the mappercomponent as part of ingesting the information; generate a tuple for atleast the first event based at least in part on the modified adapter;and provide the tuple to an event server.
 15. The system of claim 14,wherein the additional component is implemented by executing anapplication programming interface corresponding to the additionalcomponent.